Matplotlib — Figures and Axes

After completing this topic, you will be able to:

Understand the Figure/Axes structure in matplotlib and create basic graphs on your own.

What is Matplotlib?

Matplotlib is a library for creating graphs and charts in Python. When you look at data visually, you can see patterns much more easily than when you just look at numbers.

python

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

plt.plot(x, y)
plt.show()

plt is the conventional abbreviation for matplotlib.pyplot.

Figure and Axes

The core structure of matplotlib consists of two main components:

text

Figure (Canvas)
└── Axes (Graph area)
    ├── x-axis
    ├── y-axis
    ├── Title
    └── Data (lines, bars, points...)

Figure: The overall drawing area. Like a canvas.
Axes: The space where the actual graph is drawn. You can place multiple Axes within a single Figure.

python

import matplotlib.pyplot as plt

# Explicitly create a Figure and Axes
fig, ax = plt.subplots()

ax.plot([1, 2, 3], [10, 20, 30])
ax.set_title("My First Plot")
ax.set_xlabel("X axis")
ax.set_ylabel("Y axis")

plt.show()

plt.subplots() creates both the Figure and Axes simultaneously. This approach is highly recommended.

Line Plot

Used to show changes over time.

python

import matplotlib.pyplot as plt

months = ["Jan", "Feb", "Mar", "Apr", "May"]
sales = [100, 120, 90, 150, 130]

fig, ax = plt.subplots(figsize=(8, 5))
ax.plot(months, sales, marker="o", color="blue", linewidth=2)
ax.set_title("Monthly Sales")
ax.set_ylabel("Sales")
ax.grid(True, alpha=0.3)

plt.show()

marker="o": Displays a circle at each data point.
figsize=(8, 5): Width 8 inches, height 5 inches.
grid(True): Displays grid lines.

Bar Chart

Used for comparing categories.

python

import matplotlib.pyplot as plt

languages = ["Python", "JS", "Java", "C++"]
users = [30, 25, 20, 15]

fig, ax = plt.subplots()
ax.bar(languages, users, color=["#3776AB", "#F7DF1E", "#B07219", "#00599C"])
ax.set_title("Programming Language Popularity")
ax.set_ylabel("Users (%)")

plt.show()

You can specify a list of colors to ax.bar() to assign different colors to each bar.

Scatter Plot

Shows the relationship between two variables.

python

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(42)
x = np.random.randn(50)
y = 2 * x + np.random.randn(50) * 0.5

fig, ax = plt.subplots()
ax.scatter(x, y, alpha=0.7, color="coral")
ax.set_title("Scatter Plot Example")
ax.set_xlabel("X")
ax.set_ylabel("Y")

plt.show()

alpha=0.7 is the transparency. Useful when many points overlap.

Multiple Graphs at Once

python

import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 3, figsize=(15, 4))

# First: Line plot
axes[0].plot([1, 2, 3], [1, 4, 9])
axes[0].set_title("Line")

# Second: Bar chart
axes[1].bar(["A", "B", "C"], [5, 3, 7])
axes[1].set_title("Bar")

# Third: Scatter plot
axes[2].scatter([1, 2, 3, 4], [4, 1, 3, 2])
axes[2].set_title("Scatter")

plt.tight_layout()
plt.show()

plt.subplots(1, 3) creates a subplot with 1 row and 3 columns. tight_layout() automatically adjusts the spacing between graphs to prevent overlapping.

Saving

python

# Save to a file instead of displaying on the screen
fig.savefig("chart.png", dpi=150, bbox_inches="tight")

dpi=150: Resolution (default 100)
bbox_inches="tight": Automatically adjusts margins
Supported formats: PNG, PDF, SVG, JPG

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matplotlib — Figure and Axes

Matplotlib — Figures and Axes

After completing this topic, you will be able to:

What is Matplotlib?

Figure and Axes

Line Plot

Bar Chart

Scatter Plot

Multiple Graphs at Once

Saving

💬 Questions & Comments